updated code ✅✅

mediSync/app.py

@@ -426,8 +426,26 @@ def create_interface():
     try:
         sample_images_dir = Path(__file__).parent.parent / "data" / "sample"
         os.makedirs(sample_images_dir, exist_ok=True)
+        
+        # Check for existing images first
         sample_images = list(sample_images_dir.glob("*.png")) + list(sample_images_dir.glob("*.jpg"))
-        if sample_images:
+        
+        if not sample_images:
+            # Use reliable fallback image URL
+            fallback_url = "https://raw.githubusercontent.com/ieee8023/covid-chestxray-dataset/master/images/1-s2.0-S0929664620300449-gr2_lrg-a.jpg"
+            sample_path = sample_images_dir / "sample_xray.jpg"
+            try:
+                response = requests.get(fallback_url, timeout=10)
+                if response.status_code == 200:
+                    with open(sample_path, 'wb') as f:
+                        f.write(response.content)
+                    sample_image_path = str(sample_path)
+                    logging.info("Successfully downloaded fallback sample image")
+                else:
+                    logging.warning("Failed to download sample image")
+            except Exception as e:
+                logging.warning(f"Could not download sample image: {str(e)}")
+        else:
             sample_image_path = str(sample_images[0])
     except Exception as e:
         logging.error(f"Error setting up sample images: {str(e)}")
@@ -436,142 +454,217 @@ def create_interface():
         title="MediSync: Multi-Modal Medical Analysis System", 
         theme=gr.themes.Soft()
     ) as interface:
-        # JavaScript to extract appointment ID from URL
-        js_extract_id = """
-        function() {
-            const params = new URLSearchParams(window.location.search);
-            return params.get('appointment_id') || '';
-        }
-        """
-        
-        # Hidden appointment ID component
-        appointment_id = gr.Textbox(visible=False)
+        # Appointment ID handling with JavaScript workaround
+        appointment_id = gr.Textbox(visible=False, value="")
         
         # Load appointment ID from URL when interface loads
         interface.load(
-            fn=None,
-            _js=js_extract_id,
-            outputs=appointment_id
+            fn=lambda: "",
+            outputs=appointment_id,
+            _js="""
+            function() {
+                const params = new URLSearchParams(window.location.search);
+                return params.get('appointment_id') || '';
+            }
+            """
         )
 
         gr.Markdown("""
         # MediSync: Multi-Modal Medical Analysis System
+        
+        This AI-powered healthcare solution combines X-ray image analysis with patient report text processing 
+        to provide comprehensive medical insights.
+        
         ## How to Use
         1. Upload a chest X-ray image
-        2. Enter medical report text
-        3. Choose analysis type
-        4. Click "End Consultation" when finished
+        2. Enter the corresponding medical report text
+        3. Choose the analysis type: image-only, text-only, or multimodal (combined)
+        4. Click "End Consultation" when finished to complete your appointment
         """)
 
         with gr.Tab("Multimodal Analysis"):
             with gr.Row():
                 with gr.Column():
                     multi_img_input = gr.Image(label="Upload X-ray Image", type="pil")
+                    multi_img_enhance = gr.Button("Enhance Image")
+
                     multi_text_input = gr.Textbox(
-                        label="Medical Report Text",
-                        value=example_report,
-                        lines=10
+                        label="Enter Medical Report Text",
+                        placeholder="Enter the radiologist's report text here...",
+                        lines=10,
+                        value=example_report if not sample_image_path else None,
+                    )
+
+                    multi_analyze_btn = gr.Button(
+                        "Analyze Image & Text", variant="primary"
                     )
-                    multi_analyze_btn = gr.Button("Analyze", variant="primary")
+
                 with gr.Column():
-                    multi_results = gr.HTML(label="Results")
+                    multi_results = gr.HTML(label="Analysis Results")
                     multi_plot = gr.HTML(label="Visualization")
 
+            if sample_image_path:
+                gr.Examples(
+                    examples=[[sample_image_path, example_report]],
+                    inputs=[multi_img_input, multi_text_input],
+                    label="Example X-ray and Report",
+                )
+
         with gr.Tab("Image Analysis"):
             with gr.Row():
                 with gr.Column():
                     img_input = gr.Image(label="Upload X-ray Image", type="pil")
-                    img_analyze_btn = gr.Button("Analyze", variant="primary")
+                    img_enhance = gr.Button("Enhance Image")
+                    img_analyze_btn = gr.Button("Analyze Image", variant="primary")
+
                 with gr.Column():
                     img_output = gr.Image(label="Processed Image")
-                    img_results = gr.HTML(label="Results")
+                    img_results = gr.HTML(label="Analysis Results")
+                    img_plot = gr.HTML(label="Visualization")
+
+            if sample_image_path:
+                gr.Examples(
+                    examples=[[sample_image_path]],
+                    inputs=[img_input],
+                    label="Example X-ray Image",
+                )
 
         with gr.Tab("Text Analysis"):
             with gr.Row():
                 with gr.Column():
                     text_input = gr.Textbox(
-                        label="Medical Report Text",
+                        label="Enter Medical Report Text",
+                        placeholder="Enter the radiologist's report text here...",
+                        lines=10,
                         value=example_report,
-                        lines=10
                     )
-                    text_analyze_btn = gr.Button("Analyze", variant="primary")
+                    text_analyze_btn = gr.Button("Analyze Text", variant="primary")
+
                 with gr.Column():
-                    text_results = gr.HTML(label="Results")
+                    text_output = gr.Textbox(label="Processed Text")
+                    text_results = gr.HTML(label="Analysis Results")
+                    text_plot = gr.HTML(label="Entity Visualization")
+
+            gr.Examples(
+                examples=[[example_report]],
+                inputs=[text_input],
+                label="Example Medical Report",
+            )
+
+        with gr.Tab("About"):
+            gr.Markdown("""
+            ## About MediSync
+            
+            MediSync is an AI-powered healthcare solution that uses multi-modal analysis to provide comprehensive insights from medical images and reports.
+            
+            ### Key Features
+            
+            - **X-ray Image Analysis**: Detects abnormalities in chest X-rays using pre-trained vision models
+            - **Medical Report Processing**: Extracts key information from patient reports using NLP models
+            - **Multi-modal Integration**: Combines insights from both image and text data for more accurate analysis
+            
+            ### Models Used
+            
+            - **X-ray Analysis**: facebook/deit-base-patch16-224-medical-cxr
+            - **Medical Text Analysis**: medicalai/ClinicalBERT
+            
+            ### Important Disclaimer
+            
+            This tool is for educational and research purposes only. It is not intended to provide medical advice or replace professional healthcare. Always consult with qualified healthcare providers for medical decisions.
+            """)
 
         # Consultation completion section
         with gr.Row():
-            end_consultation_btn = gr.Button(
-                "End Consultation", 
-                variant="stop",
-                size="lg"
-            )
-            completion_status = gr.HTML()
+            with gr.Column():
+                end_consultation_btn = gr.Button(
+                    "End Consultation", 
+                    variant="stop",
+                    size="lg"
+                )
+                completion_status = gr.HTML()
+
+        # Set up event handlers
+        multi_img_enhance.click(
+            app.enhance_image, inputs=multi_img_input, outputs=multi_img_input
+        )
+        multi_analyze_btn.click(
+            app.analyze_multimodal,
+            inputs=[multi_img_input, multi_text_input],
+            outputs=[multi_results, multi_plot],
+        )
 
-        def complete_consultation(app_id):
-            print(f"Processing completion for appointment: {app_id}")
+        img_enhance.click(app.enhance_image, inputs=img_input, outputs=img_output)
+        img_analyze_btn.click(
+            app.analyze_image,
+            inputs=img_input,
+            outputs=[img_output, img_results, img_plot],
+        )
+
+        text_analyze_btn.click(
+            app.analyze_text,
+            inputs=text_input,
+            outputs=[text_output, text_results, text_plot],
+        )
+
+        def complete_consultation(appointment_id):
+            """Handle consultation completion."""
+            print(f"DEBUG - Appointment ID: {appointment_id}")  # Debug output
             
-            if not app_id:
-                return "<div class='alert alert-error'>No appointment ID found</div>"
+            if not appointment_id:
+                return "<div class='alert alert-error'>No appointment ID found. Please contact support.</div>"
             
             try:
+                # Update to your actual Flask server URL
+                flask_app_url = "http://127.0.0.1:600/complete_appointment"
+                
                 response = requests.post(
-                    "http://127.0.0.1:600/complete_appointment",
-                    json={"appointment_id": app_id},
+                    flask_app_url,
+                    json={"appointment_id": appointment_id},
                     timeout=10
                 )
                 
                 if response.status_code == 200:
                     return """
                     <div class='alert alert-success'>
-                        Completed! Redirecting...
+                        Consultation completed successfully. Redirecting...
                         <script>
-                            setTimeout(() => {
+                            setTimeout(function() {
                                 window.location.href = "http://127.0.0.1:600/doctors#consultations";
                             }, 2000);
                         </script>
                     </div>
                     """
-                return f"""
-                <div class='alert alert-error'>
-                    Error: {response.json().get('message', 'Unknown error')}
-                </div>
-                """
+                else:
+                    return f"""
+                    <div class='alert alert-error'>
+                        Error completing appointment (Status: {response.status_code}). 
+                        Please contact support.
+                    </div>
+                    """
+                    
             except Exception as e:
                 return f"""
                 <div class='alert alert-error'>
-                    Connection error: {str(e)}
+                    Error: {str(e)}
                 </div>
                 """
 
         end_consultation_btn.click(
             fn=complete_consultation,
-            inputs=appointment_id,
+            inputs=[appointment_id],
             outputs=completion_status
         )
 
-        # Analysis button handlers
-        multi_analyze_btn.click(
-            app.analyze_multimodal,
-            inputs=[multi_img_input, multi_text_input],
-            outputs=[multi_results, multi_plot]
-        )
-        img_analyze_btn.click(
-            app.analyze_image,
-            inputs=img_input,
-            outputs=[img_output, img_results]
-        )
-        text_analyze_btn.click(
-            app.analyze_text,
-            inputs=text_input,
-            outputs=text_results
-        )
-
     try:
         interface.launch()
     except Exception as e:
         logging.error(f"Failed to launch interface: {str(e)}")
-        raise
+        raise RuntimeError("Failed to launch MediSync interface") from e
+
 
 if __name__ == "__main__":
-    logging.basicConfig(level=logging.INFO)
+    logging.basicConfig(
+        level=logging.INFO,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+    )
     create_interface()